Reservoir simulations can be interfaced with surface facility network simulations to more accurately predict the interactions between wells and external surface facilities. In general, “reservoir simulations” refer to mathematical representations of fluid flow (e.g., oil, gas, water) in a physical subterranean reservoir and “surface facility network simulations” refer to mathematical representations of fluid flow through production equipment. For example, in deepwater oil and gas field development, wells from different reservoirs often flow through pipelines to a shared surface facility platform before being transported by a pipeline to the sale point. These facilities may consist of a network of flowlines from the wellheads joining at manifolds to form a gathering system and, for offshore fields, the risers that take the fluids up to the facilities on the platforms. Pressure losses in the surface production system can have a critical impact on well productivity. Therefore, it is highly advantageous for the simulation model to encompass both the reservoir and the surface facilities while performing simulations for field development planning and optimization.
Many software tools have been developed to integrate the modeling of reservoirs and surface facilities. For example, the concept of a simulation model combining both reservoir and surface facility calculations, applied to a gas-water system, is known in the art. A combined reservoir and surface facility simulator applicable to large offshore oil reservoirs producing through a gathering system network has also been published. This simulation method balances the facility network and reservoir models once per timestep using an estimated mid-timestep average of the reservoir conditions. The resulting well rates are then used as control targets for the wells over the timestep. A combined system in which the network is coupled explicitly to the well-reservoir system at the wellheads was also implemented in a commercial black oil reservoir simulator.
The concept of coupled reservoir and network models has also been extended to compositional simulation. For example, an implicit procedure has been published in which the conditions in the nodes of the network are solved simultaneously with the reservoir grid. Numerical derivatives of the pipeline pressure drops are used because multiphase flow correlations are hot always amenable to analytic differentiation. This approach was applied to build an integrated compositional model of the reservoir, well tubing strings, and surface pipeline network. This approach has further been refined for history matching the network model and optimization.
An alternative approach of coupling a separate, stand-alone network model to a reservoir simulator has also been pursued. The term “coupling,” as used herein, is defined as being operatively linked or interconnected, such that the information from the separate, stand-alone surface facilities network model is utilized by the reservoir simulator during operation, and/or vice versa. Accordingly, “coupling” allows for communication between the separate simulators by sharing of data, such as through exchange of boundary conditions. Several fully featured stand-alone software products have been developed for modeling surface facilities and pipeline networks. These software products offer a choice of engineering correlations to compute pressure and temperature losses along the pipes and through the equipment components. They also include a graphical user interface for constructing the model. Further developments to reservoir simulators that provide greater flexibility in the data exchange with these network simulators and improve the performance of the coupling methods have also been made. Accordingly, direct use of these products is available instead of reproducing their features within the reservoir simulator, which would require substantial coding effort.
More recent advances have focused on the following diverse strategies:                A unified formulation in which the surface facility network is represented by an extension of the reservoir simulator's implicit well model.        Coupling separate reservoir and surface facility models by exchanging boundary conditions. Reservoir and surface facility network simulations are modeled separately using different applications, but integrated using externally coupled workflows that rely on exchanging Inflow Performance Relationships (IPRs) at the coupling points.        
A unified model has been developed in which the simulator's discretized well model is extended to include the surface facility network. The network is thus solved simultaneously with the wells, and the equations modeling the well-network system are implicitly coupled to the reservoir model as a single system. An alternative formulation for the network equations has also been proposed such that they are placed in a similar form to the reservoir equations, thereby facilitating their solution by efficient linear solvers already developed for reservoir simulation. An approach using slack variables to the problem of determining which flow rate or pressure constraints are active at any time in a unified model where constraints can be applied at any location has also been developed.
With regards to the strategy of coupling separate reservoir and surface facility models, each of the examples referenced above have coupled a particular facility simulator to a particular reservoir simulator, without offering a choice of software products. To allow a selection of facility simulators to be coupled to a selection of reservoir simulators, a third software product called a “controller” has been developed. The controller is responsible for overseeing the coupled solution of the various domain models (reservoir and surface facilities), managing the exchange of boundary conditions between them, and advancing the global system through time. The individual domain models may have different fluid representations, such as black oil or compositional. The production streams from the models with the less detailed fluid representations are converted into the more detailed representation by a delumping process. This strategy of coupling separate surface and reservoir domain models by a field management controller has been implemented into a commercial simulator.
These two strategies have their own distinct advantages and disadvantages. The principal advantage of the unified strategy is that the complete network-well-reservoir system can be solved simultaneously in a fully-implicit numerical scheme, thereby retaining stability over the long timesteps desired in reservoir simulation. However, the features required for modeling surface facility networks have to be implemented in the reservoir simulator. The strategy of coupling separate software models offers the advantage of software choice. In principle, any third-party surface facilities simulator can be coupled to the system provided that a communications interface has been implemented to enable the exchange of boundary conditions and instructions. Thus, all of the tools and options available in the fully-featured surface facilities simulator are available for use without having to duplicate their implementation in the reservoir simulator.
The principal disadvantage of the coupled software strategy typically lies in the numerical stability of the coupling scheme. The separate surface facilities model is not solved simultaneously with the reservoir model as a single fully-implicit system. Instead, a timestep lagged or an iteratively lagged coupling scheme is used. A timestep lagged coupling scheme balances the system at the beginning of each timestep. The resulting conditions at the wells (the flow rate, bottomhole pressure, or tubing head pressure) are applied as well constraints while the reservoir simulation is advanced through time. Alternatively, the coupling may be carried out periodically with a predefined period length, which does not necessarily correspond to the timestep length used in the reservoir simulation. In either case, since the reservoir conditions evolve over the timestep, the applied well constraints might not accurately represent the balanced solution at the end of the timestep. For example, if the timestep between balancing calculations is too long, numerical instability may result and the well rates will likely oscillate from one timestep to the next.
An iteratively lagged coupling scheme rebalances the system at each iteration of the reservoir solution. However, the absence in the reservoir simulator's Jacobian matrix of derivatives representing the influence of the network will, in general, impede the convergence of the reservoir solution. Accordingly, the balancing process is typically performed only in the first few iterations of the reservoir solution, leaving the well constraints constant for the remaining iterations to assist convergence. Shortening the timestep will increase the accuracy of these coupling schemes and reduce the likelihood of instability, but at the expense of increasing the overall CPU time.
Therefore, previous coupled systems have exhibited instabilities due to the coupling calculated at the beginning of a timestep not being representative of the coupling at the end of the timestep. A method is needed that has all the advantages of external coupling, but eliminates some of its disadvantages, namely large balancing errors and possible oscillations resulting from the explicit approach.